# -*- coding: utf-8 -*-
from utils.operators.cluster_for_spark_sql_operator import SparkSqlOperator
from datetime import timedelta
#from jms_dm_duty.dm.dm_waybill_collect_intime_dt import jms_dm__dm_waybill_collect_intime_dt

jms_dm__dm_waybiil_ticket_violation_cost_dt = SparkSqlOperator(
    task_id='jms_dm__dm_waybiil_ticket_violation_cost_dt',
    task_concurrency=1,
    pool_slots=2,
    master='yarn',
    execution_timeout = timedelta(minutes=120),
    email=['matthew.xiong@jtexpress.com', 'yl_bigdata@yl-scm.com'],
    name='jms_dm__dm_waybiil_ticket_violation_cost_dt_{{ execution_date | date_add(1) | cst_ds }}',
    sql='jms_dm_duty/dm/dm_waybiil_ticket_violation_cost_dt/execute.hql',
    driver_memory='2G',
    executor_cores=2,
    executor_memory='10G',
    num_executors=5,  # spark.dynamicAllocation.enabled 为 True 时，num_executors 表示最少 Executor 数
    conf={
        'spark.dynamicAllocation.enabled': 'true',  # 动态资源开启
        'spark.shuffle.service.enabled' : 'true',  # 动态资源 Shuffle 服务开启
        'spark.dynamicAllocation.maxExecutors' : 5,  # 动态资源最大扩容 Executor 数
        'spark.dynamicAllocation.cachedExecutorIdleTimeout': 60,  # 动态资源自动释放闲置 Executor 的超时时间(s)
        'spark.sql.sources.partitionOverwriteMode' : 'dynamic',  # 允许删改已存在的分区
        'spark.executor.memoryOverhead' : '6G',  # 堆外内存
        'spark.sql.shuffle.partitions' : 100,
    },
    #hiveconf={
    #    'hive.exec.dynamic.partition' : 'true',  # 动态分区
    #    'hive.exec.dynamic.partition.mode' : 'nonstrict',
    #    'hive.exec.max.dynamic.partitions' : 400,  # 每天生成 20 个分区
    #    'hive.exec.max.dynamic.partitions.pernode': 400,  # 每天生成 20 个分区
    #},
    yarn_queue='route',
)

#jms_dm__dm_waybiil_ticket_violation_cost_dt << jms_dm__dm_waybill_collect_intime_dt